{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.导入工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "\n",
    "import numpy as np    # 矩阵操作\n",
    "import pandas as pd   # SQL数据处理\n",
    "import matplotlib.pyplot as plt  #画图\n",
    "import seaborn as sns    #画图\n",
    "\n",
    "from sklearn.metrics import r2_score #评价回归预测模型的性能\n",
    "\n",
    "#图形出现在Notebook里而不是新窗口\n",
    "%matplotlib inline  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.数据探索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1导入数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities    ...     PoolArea PoolQC Fence MiscFeature MiscVal  \\\n",
       "0         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "1         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "2         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "3         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "4         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "\n",
       "  MoSold YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0      2   2008        WD         Normal     208500  \n",
       "1      5   2007        WD         Normal     181500  \n",
       "2      9   2008        WD         Normal     223500  \n",
       "3      2   2006        WD        Abnorml     140000  \n",
       "4     12   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "dataPath = './JupyterData/'\n",
    "#训练数据\n",
    "trainData = pd.read_csv(dataPath+\"Ames_House_train.csv\")\n",
    "#测试数据\n",
    "testData = pd.read_csv(dataPath+\"Ames_House_test.csv\")\n",
    "#显示前5行数据\n",
    "trainData.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>1456</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>62.0</td>\n",
       "      <td>7917</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>175000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>1457</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>85.0</td>\n",
       "      <td>13175</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1457</th>\n",
       "      <td>1458</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>66.0</td>\n",
       "      <td>9042</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GdPrv</td>\n",
       "      <td>Shed</td>\n",
       "      <td>2500</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>266500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>1459</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>9717</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>142125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1459</th>\n",
       "      <td>1460</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>75.0</td>\n",
       "      <td>9937</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>147500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "1455  1456          60       RL         62.0     7917   Pave   NaN      Reg   \n",
       "1456  1457          20       RL         85.0    13175   Pave   NaN      Reg   \n",
       "1457  1458          70       RL         66.0     9042   Pave   NaN      Reg   \n",
       "1458  1459          20       RL         68.0     9717   Pave   NaN      Reg   \n",
       "1459  1460          20       RL         75.0     9937   Pave   NaN      Reg   \n",
       "\n",
       "     LandContour Utilities    ...     PoolArea PoolQC  Fence MiscFeature  \\\n",
       "1455         Lvl    AllPub    ...            0    NaN    NaN         NaN   \n",
       "1456         Lvl    AllPub    ...            0    NaN  MnPrv         NaN   \n",
       "1457         Lvl    AllPub    ...            0    NaN  GdPrv        Shed   \n",
       "1458         Lvl    AllPub    ...            0    NaN    NaN         NaN   \n",
       "1459         Lvl    AllPub    ...            0    NaN    NaN         NaN   \n",
       "\n",
       "     MiscVal MoSold YrSold  SaleType  SaleCondition  SalePrice  \n",
       "1455       0      8   2007        WD         Normal     175000  \n",
       "1456       0      2   2010        WD         Normal     210000  \n",
       "1457    2500      5   2010        WD         Normal     266500  \n",
       "1458       0      4   2010        WD         Normal     142125  \n",
       "1459       0      6   2008        WD         Normal     147500  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#显示后5行数据\n",
    "trainData.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "#显示每列空值数目\n",
    "# trainData.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 可以看到许多特征有空值，需要做数据填补"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2显示数据基本信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1460 entries, 0 to 1459\n",
      "Data columns (total 81 columns):\n",
      "Id               1460 non-null int64\n",
      "MSSubClass       1460 non-null int64\n",
      "MSZoning         1460 non-null object\n",
      "LotFrontage      1201 non-null float64\n",
      "LotArea          1460 non-null int64\n",
      "Street           1460 non-null object\n",
      "Alley            91 non-null object\n",
      "LotShape         1460 non-null object\n",
      "LandContour      1460 non-null object\n",
      "Utilities        1460 non-null object\n",
      "LotConfig        1460 non-null object\n",
      "LandSlope        1460 non-null object\n",
      "Neighborhood     1460 non-null object\n",
      "Condition1       1460 non-null object\n",
      "Condition2       1460 non-null object\n",
      "BldgType         1460 non-null object\n",
      "HouseStyle       1460 non-null object\n",
      "OverallQual      1460 non-null int64\n",
      "OverallCond      1460 non-null int64\n",
      "YearBuilt        1460 non-null int64\n",
      "YearRemodAdd     1460 non-null int64\n",
      "RoofStyle        1460 non-null object\n",
      "RoofMatl         1460 non-null object\n",
      "Exterior1st      1460 non-null object\n",
      "Exterior2nd      1460 non-null object\n",
      "MasVnrType       1452 non-null object\n",
      "MasVnrArea       1452 non-null float64\n",
      "ExterQual        1460 non-null object\n",
      "ExterCond        1460 non-null object\n",
      "Foundation       1460 non-null object\n",
      "BsmtQual         1423 non-null object\n",
      "BsmtCond         1423 non-null object\n",
      "BsmtExposure     1422 non-null object\n",
      "BsmtFinType1     1423 non-null object\n",
      "BsmtFinSF1       1460 non-null int64\n",
      "BsmtFinType2     1422 non-null object\n",
      "BsmtFinSF2       1460 non-null int64\n",
      "BsmtUnfSF        1460 non-null int64\n",
      "TotalBsmtSF      1460 non-null int64\n",
      "Heating          1460 non-null object\n",
      "HeatingQC        1460 non-null object\n",
      "CentralAir       1460 non-null object\n",
      "Electrical       1459 non-null object\n",
      "1stFlrSF         1460 non-null int64\n",
      "2ndFlrSF         1460 non-null int64\n",
      "LowQualFinSF     1460 non-null int64\n",
      "GrLivArea        1460 non-null int64\n",
      "BsmtFullBath     1460 non-null int64\n",
      "BsmtHalfBath     1460 non-null int64\n",
      "FullBath         1460 non-null int64\n",
      "HalfBath         1460 non-null int64\n",
      "BedroomAbvGr     1460 non-null int64\n",
      "KitchenAbvGr     1460 non-null int64\n",
      "KitchenQual      1460 non-null object\n",
      "TotRmsAbvGrd     1460 non-null int64\n",
      "Functional       1460 non-null object\n",
      "Fireplaces       1460 non-null int64\n",
      "FireplaceQu      770 non-null object\n",
      "GarageType       1379 non-null object\n",
      "GarageYrBlt      1379 non-null float64\n",
      "GarageFinish     1379 non-null object\n",
      "GarageCars       1460 non-null int64\n",
      "GarageArea       1460 non-null int64\n",
      "GarageQual       1379 non-null object\n",
      "GarageCond       1379 non-null object\n",
      "PavedDrive       1460 non-null object\n",
      "WoodDeckSF       1460 non-null int64\n",
      "OpenPorchSF      1460 non-null int64\n",
      "EnclosedPorch    1460 non-null int64\n",
      "3SsnPorch        1460 non-null int64\n",
      "ScreenPorch      1460 non-null int64\n",
      "PoolArea         1460 non-null int64\n",
      "PoolQC           7 non-null object\n",
      "Fence            281 non-null object\n",
      "MiscFeature      54 non-null object\n",
      "MiscVal          1460 non-null int64\n",
      "MoSold           1460 non-null int64\n",
      "YrSold           1460 non-null int64\n",
      "SaleType         1460 non-null object\n",
      "SaleCondition    1460 non-null object\n",
      "SalePrice        1460 non-null int64\n",
      "dtypes: float64(3), int64(35), object(43)\n",
      "memory usage: 924.0+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(1460, 81)"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainData.info()\n",
    "trainData.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 许多特征为object类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1459 entries, 0 to 1458\n",
      "Data columns (total 80 columns):\n",
      "Id               1459 non-null int64\n",
      "MSSubClass       1459 non-null int64\n",
      "MSZoning         1455 non-null object\n",
      "LotFrontage      1232 non-null float64\n",
      "LotArea          1459 non-null int64\n",
      "Street           1459 non-null object\n",
      "Alley            107 non-null object\n",
      "LotShape         1459 non-null object\n",
      "LandContour      1459 non-null object\n",
      "Utilities        1457 non-null object\n",
      "LotConfig        1459 non-null object\n",
      "LandSlope        1459 non-null object\n",
      "Neighborhood     1459 non-null object\n",
      "Condition1       1459 non-null object\n",
      "Condition2       1459 non-null object\n",
      "BldgType         1459 non-null object\n",
      "HouseStyle       1459 non-null object\n",
      "OverallQual      1459 non-null int64\n",
      "OverallCond      1459 non-null int64\n",
      "YearBuilt        1459 non-null int64\n",
      "YearRemodAdd     1459 non-null int64\n",
      "RoofStyle        1459 non-null object\n",
      "RoofMatl         1459 non-null object\n",
      "Exterior1st      1458 non-null object\n",
      "Exterior2nd      1458 non-null object\n",
      "MasVnrType       1443 non-null object\n",
      "MasVnrArea       1444 non-null float64\n",
      "ExterQual        1459 non-null object\n",
      "ExterCond        1459 non-null object\n",
      "Foundation       1459 non-null object\n",
      "BsmtQual         1415 non-null object\n",
      "BsmtCond         1414 non-null object\n",
      "BsmtExposure     1415 non-null object\n",
      "BsmtFinType1     1417 non-null object\n",
      "BsmtFinSF1       1458 non-null float64\n",
      "BsmtFinType2     1417 non-null object\n",
      "BsmtFinSF2       1458 non-null float64\n",
      "BsmtUnfSF        1458 non-null float64\n",
      "TotalBsmtSF      1458 non-null float64\n",
      "Heating          1459 non-null object\n",
      "HeatingQC        1459 non-null object\n",
      "CentralAir       1459 non-null object\n",
      "Electrical       1459 non-null object\n",
      "1stFlrSF         1459 non-null int64\n",
      "2ndFlrSF         1459 non-null int64\n",
      "LowQualFinSF     1459 non-null int64\n",
      "GrLivArea        1459 non-null int64\n",
      "BsmtFullBath     1457 non-null float64\n",
      "BsmtHalfBath     1457 non-null float64\n",
      "FullBath         1459 non-null int64\n",
      "HalfBath         1459 non-null int64\n",
      "BedroomAbvGr     1459 non-null int64\n",
      "KitchenAbvGr     1459 non-null int64\n",
      "KitchenQual      1458 non-null object\n",
      "TotRmsAbvGrd     1459 non-null int64\n",
      "Functional       1457 non-null object\n",
      "Fireplaces       1459 non-null int64\n",
      "FireplaceQu      729 non-null object\n",
      "GarageType       1383 non-null object\n",
      "GarageYrBlt      1381 non-null float64\n",
      "GarageFinish     1381 non-null object\n",
      "GarageCars       1458 non-null float64\n",
      "GarageArea       1458 non-null float64\n",
      "GarageQual       1381 non-null object\n",
      "GarageCond       1381 non-null object\n",
      "PavedDrive       1459 non-null object\n",
      "WoodDeckSF       1459 non-null int64\n",
      "OpenPorchSF      1459 non-null int64\n",
      "EnclosedPorch    1459 non-null int64\n",
      "3SsnPorch        1459 non-null int64\n",
      "ScreenPorch      1459 non-null int64\n",
      "PoolArea         1459 non-null int64\n",
      "PoolQC           3 non-null object\n",
      "Fence            290 non-null object\n",
      "MiscFeature      51 non-null object\n",
      "MiscVal          1459 non-null int64\n",
      "MoSold           1459 non-null int64\n",
      "YrSold           1459 non-null int64\n",
      "SaleType         1458 non-null object\n",
      "SaleCondition    1459 non-null object\n",
      "dtypes: float64(11), int64(26), object(43)\n",
      "memory usage: 912.0+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(1459, 80)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testData.info()\n",
    "testData.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 测试集没有y,暂且用训练集来交叉验证"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3查看数据特征的分布\n",
    "数量、均值、标准差、最小a值、四分之一分位数、中分位数、四分之三分位数、最大值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>...</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1452.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>730.500000</td>\n",
       "      <td>56.897260</td>\n",
       "      <td>70.049958</td>\n",
       "      <td>10516.828082</td>\n",
       "      <td>6.099315</td>\n",
       "      <td>5.575342</td>\n",
       "      <td>1971.267808</td>\n",
       "      <td>1984.865753</td>\n",
       "      <td>103.685262</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>...</td>\n",
       "      <td>94.244521</td>\n",
       "      <td>46.660274</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>43.489041</td>\n",
       "      <td>6.321918</td>\n",
       "      <td>2007.815753</td>\n",
       "      <td>180921.195890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>421.610009</td>\n",
       "      <td>42.300571</td>\n",
       "      <td>24.284752</td>\n",
       "      <td>9981.264932</td>\n",
       "      <td>1.382997</td>\n",
       "      <td>1.112799</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>181.066207</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>...</td>\n",
       "      <td>125.338794</td>\n",
       "      <td>66.256028</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>496.123024</td>\n",
       "      <td>2.703626</td>\n",
       "      <td>1.328095</td>\n",
       "      <td>79442.502883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1872.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "      <td>34900.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>365.750000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>7553.500000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1954.000000</td>\n",
       "      <td>1967.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2007.000000</td>\n",
       "      <td>129975.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>730.500000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>9478.500000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1973.000000</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>383.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>163000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1095.250000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>11601.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>712.250000</td>\n",
       "      <td>...</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>214000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>313.000000</td>\n",
       "      <td>215245.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>5644.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>857.000000</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>552.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>738.000000</td>\n",
       "      <td>15500.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>755000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Id   MSSubClass  LotFrontage        LotArea  OverallQual  \\\n",
       "count  1460.000000  1460.000000  1201.000000    1460.000000  1460.000000   \n",
       "mean    730.500000    56.897260    70.049958   10516.828082     6.099315   \n",
       "std     421.610009    42.300571    24.284752    9981.264932     1.382997   \n",
       "min       1.000000    20.000000    21.000000    1300.000000     1.000000   \n",
       "25%     365.750000    20.000000    59.000000    7553.500000     5.000000   \n",
       "50%     730.500000    50.000000    69.000000    9478.500000     6.000000   \n",
       "75%    1095.250000    70.000000    80.000000   11601.500000     7.000000   \n",
       "max    1460.000000   190.000000   313.000000  215245.000000    10.000000   \n",
       "\n",
       "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  \\\n",
       "count  1460.000000  1460.000000   1460.000000  1452.000000  1460.000000   \n",
       "mean      5.575342  1971.267808   1984.865753   103.685262   443.639726   \n",
       "std       1.112799    30.202904     20.645407   181.066207   456.098091   \n",
       "min       1.000000  1872.000000   1950.000000     0.000000     0.000000   \n",
       "25%       5.000000  1954.000000   1967.000000     0.000000     0.000000   \n",
       "50%       5.000000  1973.000000   1994.000000     0.000000   383.500000   \n",
       "75%       6.000000  2000.000000   2004.000000   166.000000   712.250000   \n",
       "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000   \n",
       "\n",
       "           ...         WoodDeckSF  OpenPorchSF  EnclosedPorch    3SsnPorch  \\\n",
       "count      ...        1460.000000  1460.000000    1460.000000  1460.000000   \n",
       "mean       ...          94.244521    46.660274      21.954110     3.409589   \n",
       "std        ...         125.338794    66.256028      61.119149    29.317331   \n",
       "min        ...           0.000000     0.000000       0.000000     0.000000   \n",
       "25%        ...           0.000000     0.000000       0.000000     0.000000   \n",
       "50%        ...           0.000000    25.000000       0.000000     0.000000   \n",
       "75%        ...         168.000000    68.000000       0.000000     0.000000   \n",
       "max        ...         857.000000   547.000000     552.000000   508.000000   \n",
       "\n",
       "       ScreenPorch     PoolArea       MiscVal       MoSold       YrSold  \\\n",
       "count  1460.000000  1460.000000   1460.000000  1460.000000  1460.000000   \n",
       "mean     15.060959     2.758904     43.489041     6.321918  2007.815753   \n",
       "std      55.757415    40.177307    496.123024     2.703626     1.328095   \n",
       "min       0.000000     0.000000      0.000000     1.000000  2006.000000   \n",
       "25%       0.000000     0.000000      0.000000     5.000000  2007.000000   \n",
       "50%       0.000000     0.000000      0.000000     6.000000  2008.000000   \n",
       "75%       0.000000     0.000000      0.000000     8.000000  2009.000000   \n",
       "max     480.000000   738.000000  15500.000000    12.000000  2010.000000   \n",
       "\n",
       "           SalePrice  \n",
       "count    1460.000000  \n",
       "mean   180921.195890  \n",
       "std     79442.502883  \n",
       "min     34900.000000  \n",
       "25%    129975.000000  \n",
       "50%    163000.000000  \n",
       "75%    214000.000000  \n",
       "max    755000.000000  \n",
       "\n",
       "[8 rows x 38 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#各属性统计特性  ()\n",
    "trainData.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.1目标特征y的直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x21009198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "sns.distplot(trainData.SalePrice.values,bins=30,kde=True) #连续型变量\n",
    "plt.rcParams['font.sans-serif']=['SimHei']      #绘图支持中文\n",
    "plt.rcParams['axes.unicode_minus']=False       #绘图支持中文\n",
    "plt.xlabel(\"房价y的直方图及核密度估计\",fontsize=12)\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 比较接近正态分布，右边远处有噪声点,可以去除噪声排除干扰"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.2目标特征y的散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c01a898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(range(trainData.shape[0]),trainData[\"SalePrice\"].values,color='purple')\n",
    "plt.title(\"房价y散点图\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.3输入特征x的直方图(由于特征较多，X只看有缺失的特征，用作数据填补的参考)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19d8ae10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.MSSubClass)  #类别型特征，离散型变量\n",
    "plt.xlabel(\"建筑类别\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c0ba9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.MSZoning)  #类别型特征，离散型变量\n",
    "plt.xlabel(\"地区分类\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1a9d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(trainData.LotArea.values,bins=50,kde=True) #连续型变量\n",
    "plt.xlabel(\"土地大小\",fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c3b3160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.Street)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"道路类型\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HV9Xadk2rI2lWu7yqfe/h7WgjNGtbXXUv//7SdhkGmi5mAv8MbFon6t00h3A2tNsOpjnMU8ByYHFVvb39xr+FdpnylwC3tM/PaDe9jeaX9xnADOAdNPcK+DTwsHa/rwA+C7ymqv4PoKq+n+Rc4PqqWpzkcTSLnC2tqp9OZidI22IYaLqYS/PNfz3w1zTf5Dd9059B8619P4CquiXJL0cB7Tf3uQP7ui/w+qr65PY+MMkLgFOBt9KcZD6PZlnzc4CvD5wc/gtg1sBbjweuoVkN1zu7aUoYBpoujgT+DPgOcD/gT9v2/Wjul/DaJAcBhyV568D77kMTIs8aaDsA+Icd+MxDgf8ceL6eJhxuoRmlvAbYh+a8wTXAgvZ2ic8Bng1ckuTyqtqI1DEvW9Mer/0F+yjgm8DLgA9W1ZJ2yfG3A99tr/y5AFhB8019Y5IDgVOr6gvAY5Nc0J5wPgb42g589O8B/7jpSVWtpwmiy4HXVtXKqvp8Vb2F5ovZXjSjh49U1Y00h7Tem+Q+974XpO1zZKDp4GnAp2iO5T8GOLU90fsp4JHAb1fV92iO5QOQ5MM0J4g3TSn4X+BM4LXA31TV3dv7wCSjNDc+WZtkBLg1yck0YXRiVf1gzFv2ZvMqt5vOQZxHM4J5OOCKt+qUq5ZqWmiPzz+4qm4eaJtdVXft5H72o5mXMOF1/0n2GnxdOyO5nDOg3ZFhIEnynIEkyTCQJGEYSJIwDCRJGAaSJOD/ARHZPTsL8pIvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4497f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.LotShape)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"房地产形状\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4a59e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.MasVnrType)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"表层砌体类型\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ac3668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.BsmtQual)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"地下室高度\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c568518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.BsmtCond)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"地下室总体状况\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4ab710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.BsmtExposure)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"地下室墙壁\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c42c908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.BsmtFinType1)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"第一类型完成面积\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7a76fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.BsmtFinType2)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"第二类型完成面积\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ee7978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.Electrical)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"电气系统\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c658cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.FireplaceQu)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"壁炉质量\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c635278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.GarageType)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"车库位置\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gTcAHgYVVdVuS1wNz2mWuBY4GngJ8h+aJAM+tql8kORI4gObehj2B/6QJmoXA56vq9O30J5MAw0CTVJK5wFnAq4AlVXX+mPmfBo4D1gFvAO6tqg+383atqvva6euqat92+hTgkk2PD0ny3ap6Sjv9ZzQH+LOBK4H9gcuAo4CLqmppz7YPBd5P80C7W4CPAH8F3F5Vv2yX+TpwBnA4MKNd/iTglzRPut0UXNJ24bOJNOkkmQ2cAyyjeff/AuD8tteQTQdc4HU0n7u9P3B1kiOAALfThAhs7i3QLvvNntf3t9t7Ak0QvBLYB/gB8Lx2mecCl7TLTQMuBL4H3NC27RM0PZGzaN79vzvJy2n+NzfS9GbOowmsm4HZwBlJPllVlz/Uv5E0lmGgyehFwDyaA+8uwOOSXEFzYL2A5gPQd6N5t/1+moeTPQn4LvB1+jyfJslzgJ8DL0nyO1X1/p7ZdwHfBv6yp7ah/f4N4Jwk51fV3UleW1W3J9kHWAqcX1WfbbcxpT1XcRlNKEETCE8EzgWOAU6lGaa6/6H9aaT+DANNOlV1Js3DAGlP0p5WVWM/RW4KzZDLde30k2jODUwDvk8zfES7jsOAf6D5vIKbgQuTvLZnez9NcjxwcLvO2cAftfNuSPJx4HjgFOATSe6nCaklwI1Jjm1XNZXmyZork9xLE1gbaXoW72p/p+XAm6rqe7/p30nqZRhoUknyauAEmnfx0DyGeH6STY8JfwTNENJ04J/b17+ieQrpPJrPj5ie5D1VdVn7M/8HvLSqftJu45U0B/Pjejb9KOB1VXV9ksvZPIS0P7Bvuw6q6tlJHk/zDn8pcCzwFppexaeqamXPOqfR/I9u6nmcDLwNeHaSqVW16jf4U0lbMAw0qVTVOTQHe+DXJ5JP7e0ZJNkXOLSqXtJTWw5c02ccPlX1rTHb2HSg77389Fc0w0E/pwmU0ATG3jTDT2clmUUzRHULzbv+KTQ9ji8CF1bVV3rWtwvNUNMxwAhwL014vZvmPMN1D+LPIk3I+ww02W16d91rlOaTrHpN7bMcwMyxhSRzk3yf5tLQTe4Fjqmqw4Er2u3uWlWfr6rTq+qeqtoAHFdVf05zwvmpNAf1g4HdklyWZE67vl3bdexCc4/By9rXh1fVqZuudpK2Fy8tlR6CJNM29RCGsK29qmr9MLalnZdhIElymEiSZBhIkjAMJEkYBpIk4P8B5+7I/yFD0OEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e7da5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.GarageFinish)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"车库内部装修\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e903630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.Fence)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"围栏质量\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e8fe978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(trainData.MiscFeature)  #类别型特征,离散型变量\n",
    "plt.xlabel(\"其他杂项\")\n",
    "plt.ylabel(\"数量\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.特征工程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1数据清洗"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1.1缺失数据非常大的几个特征直接删除(如PoolQC，1460条数据就3条有值)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [],
   "source": [
    "#所有缺失数据的特征列\n",
    "miss_colums=['LotFrontage','Alley','MasVnrType','MasVnrArea','BsmtQual','BsmtCond','BsmtExposure','BsmtFinType1','BsmtFinType2',\n",
    "                'Electrical','FireplaceQu','GarageType','GarageYrBlt','GarageFinish','GarageQual','GarageCond','PoolQC','Fence','MiscFeature']\n",
    "\n",
    "#直接删除的特征列\n",
    "detete_colms=['Alley','GarageQual','GarageCond','PoolQC']\n",
    "for colms_a in detete_colms:\n",
    "    trainData=trainData.drop(colms_a,axis=1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1.2通过数据探索时的直方图与统计图，用众数去填补数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id               0\n",
       "MSSubClass       0\n",
       "MSZoning         0\n",
       "LotFrontage      0\n",
       "LotArea          0\n",
       "Street           0\n",
       "LotShape         0\n",
       "LandContour      0\n",
       "Utilities        0\n",
       "LotConfig        0\n",
       "LandSlope        0\n",
       "Neighborhood     0\n",
       "Condition1       0\n",
       "Condition2       0\n",
       "BldgType         0\n",
       "HouseStyle       0\n",
       "OverallQual      0\n",
       "OverallCond      0\n",
       "YearBuilt        0\n",
       "YearRemodAdd     0\n",
       "RoofStyle        0\n",
       "RoofMatl         0\n",
       "Exterior1st      0\n",
       "Exterior2nd      0\n",
       "MasVnrType       0\n",
       "MasVnrArea       0\n",
       "ExterQual        0\n",
       "ExterCond        0\n",
       "Foundation       0\n",
       "BsmtQual         0\n",
       "                ..\n",
       "BsmtHalfBath     0\n",
       "FullBath         0\n",
       "HalfBath         0\n",
       "BedroomAbvGr     0\n",
       "KitchenAbvGr     0\n",
       "KitchenQual      0\n",
       "TotRmsAbvGrd     0\n",
       "Functional       0\n",
       "Fireplaces       0\n",
       "FireplaceQu      0\n",
       "GarageType       0\n",
       "GarageYrBlt      0\n",
       "GarageFinish     0\n",
       "GarageCars       0\n",
       "GarageArea       0\n",
       "PavedDrive       0\n",
       "WoodDeckSF       0\n",
       "OpenPorchSF      0\n",
       "EnclosedPorch    0\n",
       "3SsnPorch        0\n",
       "ScreenPorch      0\n",
       "PoolArea         0\n",
       "Fence            0\n",
       "MiscFeature      0\n",
       "MiscVal          0\n",
       "MoSold           0\n",
       "YrSold           0\n",
       "SaleType         0\n",
       "SaleCondition    0\n",
       "SalePrice        0\n",
       "Length: 77, dtype: int64"
      ]
     },
     "execution_count": 328,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#引入统计函数库\n",
    "#from scipy.stats import mode\n",
    "\n",
    "# #定义一个求众数的方法(此方法对有空行的特征，会抛异常)\n",
    "# def get_most_values(dataFrame,colmun):\n",
    "#     return mode(dataFrame[colmun]).mode[0]\n",
    "\n",
    "\n",
    "#数据填补构造器，用众数填补缺失值(此构造器只适用于数值型特征的填补)\n",
    "# impl=Imputer(missing_values=np.nan , strategy='most_frequent', axis=0) \n",
    "# trainData=impl.fit_transform(trainData)\n",
    "\n",
    "#用众数填补的特征列\n",
    "input_colums=['LotFrontage','MasVnrType','MasVnrArea','BsmtQual','BsmtCond','BsmtExposure','BsmtFinType1','BsmtFinType2',\n",
    "                'Electrical','FireplaceQu','GarageType','GarageYrBlt','GarageFinish','Fence','MiscFeature']\n",
    "\n",
    "trainData['LotFrontage'].fillna(70.0,inplace=True)\n",
    "trainData['MasVnrType'].fillna('None',inplace=True)\n",
    "trainData['MasVnrArea'].fillna(103.68,inplace=True)\n",
    "trainData['BsmtQual'].fillna('TA',inplace=True)\n",
    "trainData['BsmtCond'].fillna('TA',inplace=True)\n",
    "trainData['BsmtExposure'].fillna('No',inplace=True)\n",
    "trainData['BsmtFinType1'].fillna('Unf',inplace=True)\n",
    "trainData['BsmtFinType2'].fillna('Unf',inplace=True)\n",
    "trainData['Electrical'].fillna('SBrkr',inplace=True)\n",
    "trainData['FireplaceQu'].fillna('Gd',inplace=True)\n",
    "trainData['GarageType'].fillna('Attchd',inplace=True)\n",
    "trainData['GarageYrBlt'].fillna(1971.00,inplace=True)\n",
    "trainData['GarageFinish'].fillna('Unf',inplace=True)\n",
    "trainData['Fence'].fillna('MnPrv',inplace=True)\n",
    "trainData['MiscFeature'].fillna('Shed',inplace=True)\n",
    "\n",
    "trainData.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1.3 去掉y的离群点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "442567.0100000005\n",
      "61815.97\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(1430, 77)"
      ]
     },
     "execution_count": 329,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#99%分位点和1%分位点\n",
    "max = np.percentile(trainData.SalePrice.values, 99)\n",
    "min = np.percentile(trainData.SalePrice.values, 1)\n",
    "print(max)\n",
    "print(min)\n",
    "# 去除噪声\n",
    "trainData = trainData[trainData.SalePrice <= max]\n",
    "trainData = trainData[trainData.SalePrice >= min]\n",
    "trainData.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2多个特征之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [],
   "source": [
    "#数据集所有的特征列\n",
    "clolums=trainData.columns\n",
    "\n",
    "#corr()计算相关系数,abs()取绝对值,通常认为大于0.5为强相关\n",
    "data_corr = trainData.corr().abs()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e87c828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#画出热图，annot=True 格子里显示数值\n",
    "plt.subplots(figsize=(35,20))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "#保存热图\n",
    "plt.savefig('房价特征相关性热图.png' )    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 找出线性强相关的特征对(系数大于0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ExterQual and ExterCond = 0.88\n",
      "OverallQual and Exterior2nd = 0.82\n",
      "Condition1 and Condition2 = 0.81\n",
      "LotShape and MasVnrArea = 0.80\n",
      "LotArea and TotalBsmtSF = 0.79\n"
     ]
    }
   ],
   "source": [
    "#相关系数阈值 0.7\n",
    "threshold = 0.7\n",
    "#强相关的特征对list\n",
    "corr_list = [] \n",
    "#shape[0]读取矩阵第一维度的长度\n",
    "size = data_corr.shape[0]  \n",
    "\n",
    "\n",
    "#从第一列特征开始，循环遍历比较下一列与本列的相关系数.存入list\n",
    "for i in range(0,size):\n",
    "    for j in range(i+1,size):      \n",
    "        if(data_corr.iloc[i,j] >=threshold and data_corr.iloc[i,j] <1 ) or (data_corr.iloc[i,j] <= -threshold ):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j])\n",
    "\n",
    "\n",
    "#按大小排序\n",
    "sort_corr_list=sorted(corr_list,key=lambda x : -abs(x[0]))\n",
    "\n",
    "#输出\n",
    "for v,i,j in sort_corr_list:\n",
    "    print(\"%s and %s = %.2f\" % (clolums[i],clolums[j],v))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 画出强相关特征对的散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e87c668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e4c5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29739e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x297e3e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29b53ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for v,i,j in sort_corr_list:\n",
    "    sns.pairplot(trainData, size=6, x_vars=clolums[i],y_vars=clolums[j] )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可看出,相关系数大的共有5对，每对保留其一即可"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1430, 72)"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#去掉高度相关的x特征对中其一特征\n",
    "trainData=trainData.drop('ExterCond',axis=1)     #ExterQual and ExterCond = 0.88\n",
    "trainData=trainData.drop('Exterior2nd',axis=1)     #OverallQual and Exterior2nd = 0.82\n",
    "trainData=trainData.drop('Condition2',axis=1)     #Condition1 and Condition2 = 0.81\n",
    "trainData=trainData.drop('TotalBsmtSF',axis=1)     #LotArea and TotalBsmtSF = 0.80\n",
    "trainData=trainData.drop('MasVnrArea',axis=1)     #LotShape and MasVnrArea = 0.79\n",
    "\n",
    "trainData.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.数据准备"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  3.1降维,去掉无用特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1430, 71)"
      ]
     },
     "execution_count": 335,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#去掉与预测无关的序号特征\n",
    "trainData=trainData.drop('Id',axis=1)\n",
    "\n",
    "trainData.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  3.2划分数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据分割训练数据与测试数据\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 原始数据中分离出特征X和输出Y\n",
    "y = trainData['SalePrice'].values\n",
    "x = trainData.drop('SalePrice',axis=1)\n",
    "\n",
    "# 随机采样20%的数据构建测试样本，其余作为训练样本\n",
    "x_train,x_test,y_train,y_test = train_test_split(x,y,random_state=33,test_size=0.3)\n",
    "x_train.shape\n",
    "\n",
    "#特征列，用于后面显示权重系数\n",
    "columns = x_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['MSSubClass', 'MSZoning', 'LotFrontage', 'LotArea', 'Street',\n",
      "       'LotShape', 'LandContour', 'Utilities', 'LotConfig', 'LandSlope',\n",
      "       'Neighborhood', 'Condition1', 'BldgType', 'HouseStyle', 'OverallQual',\n",
      "       'OverallCond', 'YearBuilt', 'YearRemodAdd', 'RoofStyle', 'RoofMatl',\n",
      "       'Exterior1st', 'MasVnrType', 'ExterQual', 'Foundation', 'BsmtQual',\n",
      "       'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinSF1',\n",
      "       'BsmtFinType2', 'BsmtFinSF2', 'BsmtUnfSF', 'Heating', 'HeatingQC',\n",
      "       'CentralAir', 'Electrical', '1stFlrSF', '2ndFlrSF', 'LowQualFinSF',\n",
      "       'GrLivArea', 'BsmtFullBath', 'BsmtHalfBath', 'FullBath', 'HalfBath',\n",
      "       'BedroomAbvGr', 'KitchenAbvGr', 'KitchenQual', 'TotRmsAbvGrd',\n",
      "       'Functional', 'Fireplaces', 'FireplaceQu', 'GarageType', 'GarageYrBlt',\n",
      "       'GarageFinish', 'GarageCars', 'GarageArea', 'PavedDrive', 'WoodDeckSF',\n",
      "       'OpenPorchSF', 'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea',\n",
      "       'Fence', 'MiscFeature', 'MiscVal', 'MoSold', 'YrSold', 'SaleType',\n",
      "       'SaleCondition'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.1类别特征独热编码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# x_train=pd.get_dummies(x_train)\n",
    "# x_train.head()\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "\n",
    "vec = DictVectorizer(sparse=False) #sparse=False意思是不用稀疏矩阵表示\n",
    "x_train = vec.fit_transform(x_train.to_dict(orient='record'));\n",
    "x_test = vec.transform(x_test.to_dict(orient='record'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.1数据标准化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.0047441   1.81213123 -0.12873096 ...  0.66919772  0.7100009\n",
      "  -1.41364368]\n",
      " [ 0.47383054 -0.80284152 -0.12873096 ...  0.83662259  0.61102988\n",
      "   0.11614802]\n",
      " [-0.2719642   1.19370986 -0.12873096 ...  0.66919772  0.31411682\n",
      "   1.64593972]\n",
      " ...\n",
      " [-0.80166293 -0.80284152 -0.12873096 ...  0.33434797 -0.18073829\n",
      "   0.88104387]\n",
      " [-0.05323288 -0.80284152 -0.12873096 ... -0.53626137 -1.46736156\n",
      "   1.64593972]\n",
      " [-0.96241727  0.98525322 -0.12873096 ...  0.7026827   0.41308784\n",
      "   0.88104387]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\lib\\site-packages\\sklearn\\utils\\validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "#构造特征与输出的标准化器\n",
    "ss_x = StandardScaler()\n",
    "ss_y = StandardScaler()\n",
    "\n",
    "#分别对训练数据及测试数据进行标准化\n",
    "x_train = ss_x.fit_transform(x_train)\n",
    "x_test = ss_x.transform(x_test)\n",
    "\n",
    "\n",
    "#reshape(m,n)构造一个新二维数组m行 n 列，-1表示此维度和变换前一致\n",
    "y_train = ss_y.fit_transform(y_train.reshape(-1,1))\n",
    "y_test = ss_y.transform(y_test.reshape(-1,1))\n",
    "print(x_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.3数据归一化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.28553319]\n",
      " [ 0.38545439]\n",
      " [ 0.1476702 ]\n",
      " ...\n",
      " [-0.62549311]\n",
      " [-0.74219701]\n",
      " [-0.02738564]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import MaxAbsScaler\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "\n",
    "#构造归一化器\n",
    "\n",
    "#ms_x=MinMaxScaler()\n",
    "#ms_y=MinMaxScaler()\n",
    "ms_x=MaxAbsScaler()\n",
    "ms_y=MaxAbsScaler()\n",
    "\n",
    "\n",
    "#分别对训练数据及测试数据进行归一化\n",
    "x_train = ms_x.fit_transform(x_train)\n",
    "x_test = ms_x.transform(x_test)\n",
    "\n",
    "\n",
    "# y_train = ms_y.fit_transform(y_train.reshape(-1,1))\n",
    "# y_test = ms_y.transform(y_test.reshape(-1,1))\n",
    "\n",
    "print(y_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5.模型确定/模型训练"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.1 最小二乘线性回归"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.1 LinearRegression模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          权重\n",
      "0        [55290461.23490507]\n",
      "1       [23060588.495302066]\n",
      "2       [0.4693455947563052]\n",
      "3    [-0.015061572194099426]\n",
      "4       [-40142253783.12316]\n",
      "5       [-47538159934.69636]\n",
      "6       [-46905615329.70851]\n",
      "7        [-47294873548.4158]\n",
      "8      [-44521408741.461754]\n",
      "9        [68288884590.96213]\n",
      "10       [67511267892.73267]\n",
      "11       [65037032943.81708]\n",
      "12       [89557736275.53714]\n",
      "13       [95556315556.14284]\n",
      "14       [97240127283.86862]\n",
      "15       [71667236666.94891]\n",
      "16      [1.7601059675216675]\n",
      "17     [0.21461248397827148]\n",
      "18       [56319583604.36363]\n",
      "19       [58882551819.74547]\n",
      "20       [46133427876.66186]\n",
      "21       [62562711308.44018]\n",
      "22       [59934025959.38743]\n",
      "23       [45081953736.97355]\n",
      "24       [41341152931.79186]\n",
      "25       [41048841749.40366]\n",
      "26       [41382911672.19237]\n",
      "27       [40505978124.99359]\n",
      "28       [40255425683.04363]\n",
      "29      [37332313859.584595]\n",
      "..                       ...\n",
      "207    [-13853763706.804451]\n",
      "208    [-17409154392.563007]\n",
      "209    [-14274105462.741673]\n",
      "210     [-17426668632.30519]\n",
      "211    [-17514239830.835827]\n",
      "212    [-21995974829.427364]\n",
      "213     [-23429473188.81371]\n",
      "214    [-23335473296.539913]\n",
      "215     [-23264973377.30393]\n",
      "216    [-19504977679.877663]\n",
      "217     [-21572975313.45632]\n",
      "218      [3355984257.523897]\n",
      "219      [3445845834.183132]\n",
      "220      [3452758263.152901]\n",
      "221     [3435477190.6831455]\n",
      "222       [3445845833.93609]\n",
      "223        [3449302048.5181]\n",
      "224     [3183173533.8802824]\n",
      "225     [3452758262.9657497]\n",
      "226      [3003450380.833129]\n",
      "227     [0.1399993896484375]\n",
      "228      [3148794148.721254]\n",
      "229     [3148794149.1386766]\n",
      "230     [0.1953268051147461]\n",
      "231       [6140513282.35813]\n",
      "232      [6140513282.222529]\n",
      "233    [0.25458288192749023]\n",
      "234    [0.26342296600341797]\n",
      "235     [0.0761723518371582]\n",
      "236  [-0.008062362670898438]\n",
      "\n",
      "[237 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "#SVM方法优化参数\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "# 使用默认配置初始化学习器\n",
    "lr = LinearRegression()\n",
    "\n",
    "# 训练优化模型参数\n",
    "lr.fit(x_train,y_train)\n",
    "\n",
    "#预测\n",
    "y_train_pred_lr=lr.predict(x_train)\n",
    "y_test_pred_lr=lr.predict(x_test)\n",
    "\n",
    "\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "# fs = pd.DataFrame({\"特征\":list(columns), \"权重\":list((lr.coef_.T))})\n",
    "# fs.sort_values(by=['权重'],ascending=False)\n",
    "fs = pd.DataFrame({\"权重\":list((lr.coef_.T))})\n",
    "print(fs)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.2根据训练好的模型及它预测的数据，与真实目标数据对比，显示评价指标分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LinearRegression模型在训练集上的R2Score为 0.9210065335510881\n",
      "LinearRegression模型在测试集上的R2Score为 -1.4567080828544303e+19\n"
     ]
    }
   ],
   "source": [
    "# 使用r2_score评价模型在测试集和训练集上的性能，并输出评估结果\n",
    "\n",
    "\n",
    "#训练集\n",
    "print('LinearRegression模型在训练集上的R2Score为', r2_score(y_train,y_train_pred_lr ))\n",
    "\n",
    "#测试集\n",
    "print('LinearRegression模型在测试集上的R2Score为', r2_score(y_test, y_test_pred_lr))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 模型在训练集上拟合的比较好，但在测试集上的R2_SCORE上效果不好"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.3残差的分布直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x26b136a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax=plt.subplots(figsize=(7,5))\n",
    "f.tight_layout()\n",
    "ax.hist(y_train - y_train_pred_lr,bins=40, label='真值与预测的残差', color='b', alpha=.5); \n",
    "ax.set_title(\"训练集的残差直方图\") \n",
    "ax.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x26ae0d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax=plt.subplots(figsize=(7,5))\n",
    "f.tight_layout()\n",
    "ax.hist(y_test - y_test_pred_lr,bins=40, label='真值与预测的残差', color='b', alpha=.5); \n",
    "ax.set_title(\"测试集的残差直方图\") \n",
    "ax.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 貌似是极个别噪声点导致的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.4预测与真值的散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2a7b3048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_train, y_train_pred_lr)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('真值')\n",
    "plt.ylabel('预测值')\n",
    "plt.title(\"训练集\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x277c1630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_test, y_test_pred_lr)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('真值')\n",
    "plt.ylabel('预测值')\n",
    "plt.title(\"测试集\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  5.2岭回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "岭回归在训练集上的R2_Score: 0.8921715219033951\n",
      "岭回归在测试集上的R2_Score: 0.8759848194775056\n"
     ]
    }
   ],
   "source": [
    "#岭回归／L2正则\n",
    "#class sklearn.linear_model.RidgeCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, \n",
    "#                                  normalize=False, scoring=None, cv=None, gcv_mode=None, \n",
    "#                                  store_cv_values=False)\n",
    "from sklearn.linear_model import  RidgeCV\n",
    "\n",
    "#设置超参数（正则参数）范围\n",
    "alphas = [ 0.001,0.01, 0.1, 1, 10,100]\n",
    "#n_alphas = 20\n",
    "#alphas = np.logspace(-5,2,n_alphas)\n",
    "\n",
    "#生成一个RidgeCV实例\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "\n",
    "#模型训练\n",
    "ridge.fit(x_train, y_train)    \n",
    "\n",
    "#预测\n",
    "y_test_pred_ridge = ridge.predict(x_test)\n",
    "y_train_pred_ridge = ridge.predict(x_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print(\"岭回归在训练集上的R2_Score:\", r2_score(y_train, y_train_pred_ridge)) \n",
    "print(\"岭回归在测试集上的R2_Score:\", r2_score(y_test, y_test_pred_ridge))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2a6075f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax=plt.subplots(figsize=(7,5))\n",
    "f.tight_layout()\n",
    "ax.hist(y_test - y_test_pred_ridge,bins=40, label='真值与预测的残差', color='b', alpha=.5); \n",
    "ax.set_title(\"测试集的残差直方图\") \n",
    "ax.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29c00588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_test, y_test_pred_ridge)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('真值')\n",
    "plt.ylabel('预测值')\n",
    "plt.title(\"测试集散点图\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2783d7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 10.0\n"
     ]
    }
   ],
   "source": [
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "#这是为了标出最佳参数的位置，不是必须\n",
    "#plt.plot(np.log10(ridge.alpha_)*np.ones(3), [0.28, 0.29, 0.30])\n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "print ('alpha is:', ridge.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "# fs = pd.DataFrame({\"特征\":list(columns), \"OLS权重\":list((lr.coef_.T)), \"岭回归权重\":list((ridge.coef_.T))})\n",
    "# fs.sort_values(by=['OLS权重'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最佳的正则参数为alpha=1.0，岭回归的模型效果不错"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5.3 LASSO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LASSO回归在训练集上的R2_Score: 0.8904074602251698\n",
      "LASSO回归在测试集上的R2_Score: 0.8856047277520057\n"
     ]
    }
   ],
   "source": [
    "#### Lasso／L1正则\n",
    "# class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, \n",
    "#                                    normalize=False, precompute=’auto’, max_iter=1000, \n",
    "#                                    tol=0.0001, copy_X=True, cv=None, verbose=False, n_jobs=1,\n",
    "#                                    positive=False, random_state=None, selection=’cyclic’)\n",
    "from sklearn.linear_model import LassoCV\n",
    "\n",
    "#设置超参数搜索范围\n",
    "# alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "\n",
    "#生成一个LassoCV实例\n",
    "# asso = LassoCV(alphas=alphas)  \n",
    "lasso = LassoCV()  \n",
    "\n",
    "\n",
    "#训练（内含CV）\n",
    "lasso.fit(x_train, y_train.ravel())  \n",
    "\n",
    "#测试\n",
    "y_test_pred_lasso = lasso.predict(x_test)\n",
    "y_train_pred_lasso = lasso.predict(x_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print(\"LASSO回归在训练集上的R2_Score:\", r2_score(y_train, y_train_pred_lasso)) \n",
    "print(\"LASSO回归在测试集上的R2_Score:\", r2_score(y_test, y_test_pred_lasso))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x26a0be80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.0024771596055383305\n"
     ]
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "# fs = pd.DataFrame({\"特征\":list(columns), \"OLS权重\":list((lr.coef_.T)), \"岭回归权重\":list((ridge.coef_.T)), \"lasso权重\":list((lasso.coef_.T))})\n",
    "# fs.sort_values(by=['OLS权重'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最佳的正则参数为alpha=0.002，LASSO的效果也不错"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
